At present, most conventional electric meters are widely used to provide an electric consumption bill information to household and corporate users for the use of electricity in last month or within a certain period of time. Although a smart meter can show the power consumption of home or an office instantly in total, yet the smart meter cannot provide the power consumption information of each individual appliance. With a lack of itemized power consumption information of different and individual appliances, users may suffer difficulties to confirm and manage the power consumption situations of the appliances and determine the causes of power consumption from individual appliances. In addition, present existing technologies are suggested to install a power consumption monitoring device at each socket as a smart meter for individual appliances. However, such design leads to a high construction cost and narrows down the willing of users to invest on smart meters to monitor individual appliances.
Therefore, a nonintrusive load monitoring (NILM) technology is invented previously by using a single electric meter to observe a change of the total voltage and current consumed by homes and companies to determine the currently used appliances and their statuses, so that this technology allows the users to know about the operating states of the appliances. In most of the conventional methods, it is assumed that the load signature (also known as signature) of the appliances can be collected and defined in advance, and then the operating states of the appliances can be detected by searching in a power consumption signature database of appliances. Although researches disclosed different detection methods and defined a number of signatures, the collection of the signatures of the appliances and the search of the appliances encounter a certain level of difficulty since there are numerous kinds of appliances in the market, and newly released appliances in the future. Moreover, the power consumption signatures of the same appliances in different houses and locations may be slightly different. The existing NILM solutions based on one average value of the power consumption signatures may not provide accurate search results.